Gold tailings sand to prepare eco-friendly ultra-high performance concrete matrix: A synergistic approach to fine aggregate-cementitious material packing density for performance enhancement

An eco-friendly ultra-high performance concrete (UHPC) matrix was prepared using graded gold tailings sand (GTS) as the sole aggregate. Based on the theory of Densified Systems Containing homogeneously arranged ultrafine Particles (DSP), this study established a D-optimal design (DOD) predictive regression model with high goodness-of-fit (R² > 0.9). It investigated the effects of mix proportions on the fluidity, mechanical properties, and wet packing density (WPD) of gold tailings sand UHPC (GTSUHPC) matrix, determining the optimal cement-to-aggregate ratio as 0.67. The most critical factor influencing GTSUHPC matrix performance was identified as silica fume content. Subsequently, a systematic investigation was conducted on the effects of varying silica fume contents (0%, 5%, 7.5%, 10%, 12.5%) on the WPD, mechanical properties, durability, microstructure, and fractal dimension of the GTSUHPC matrix. Results indicated that at 10% silica fume content, the GTSUHPC matrix achieves maximum WPD of 0.779, enabling compact packing of cementitious materials. Its 28-day compressive and flexural strengths reached 122.0 MPa and 20.8 MPa, respectively. Its freeze-thaw resistance and sulfate erosion resistance both achieved optimal performance. Microstructural analysis indicated that the GTSUHPC matrix exhibited a denser internal structure and a richer variety of hydration products. Additionally, the fractal dimension reached its maximum value of 2.091. Moreover, WPD exhibited significant linear correlations with both mechanical properties and durability performance. This study achieved a dense packing of aggregates and cementitious materials, providing not only a theoretical basis for optimizing the performance of UHPC but also offering a practical new approach. This approach can effectively reduce manufacturing cost, decrease cement consumption, and lower carbon emissions, while also offering novel insights for the large-scale application of GTS.